Lucasfilm Ent Co Ltd, LLC Payroll Svc is hiring a Staff Data Engineer (Audio/ML) to help build scalable data infrastructure that accelerates immersive audio AI and ML research. This hybrid role in Nicasio, CA focuses on end-to-end pipelines for ingesting, preprocessing, transforming, and curating large-scale audio datasets, enabling repeatable training, retraining, and evaluation workflows. You will also apply advanced audio preprocessing techniques to support formats such as Dolby Atmos and high-order ambisonics.
Compensation for this role is USD 173,100 - 232,100 per year.
What you’ll do
- Design and maintain scalable automated pipelines for ingestion, preprocessing, and transformation of large-scale audio datasets.
- Support efficient model training and retraining workflows so teams can continuously improve AI/ML models.
- Partner with AI/ML researchers to define data requirements and incorporate feedback to strengthen pipeline functionality.
- Develop advanced preprocessing for immersive and multichannel audio formats (including Dolby Atmos and high-order ambisonics).
- Automate dataset preparation such as cleaning, normalization, and augmentation for different model architectures, including foundational models and transformers.
- Integrate external datasets and APIs while adhering to legal and ethical data usage standards.
- Monitor and optimize pipeline performance to effectively handle complex and dynamic data structures.
- Build dataset annotation and curation workflows, including tools for labeling and using active learning methods.
- Run exploratory data analysis to identify trends, validate dataset quality, and surface data gaps.
What you bring
- Master’s Degree, with preference for a PhD in Data Engineering/Science, Computer Science, Signal Processing, or a related field.
- 8+ years of experience in data engineering or data science, focused on building pipelines for AI/ML applications.
- Strong Python proficiency, including experience with Pandas, NumPy, and PyTorch data utilities.
- Hands-on audio processing experience with tools such as Librosa, FFmpeg, and SoX for complex audio formats.
- Experience with scalable pipeline tooling including GitLab, Apache Spark, Airflow, or Luigi, plus containerized workflows using Docker and Kubernetes.
- Understanding of data pipeline needs for iterative training, retraining, and evaluation in research workflows.
- Experience with immersive and multichannel audio formats.
- Knowledge of cloud platforms and storage/processing tools such as AWS S3, Redshift, or Google BigQuery.
- Strong problem-solving skills with a proactive mindset for evolving data challenges.
Tools and technologies you’ll use
Python, Pandas, NumPy, PyTorch, Librosa, FFmpeg, SoX, GitLab, Apache Spark, Airflow, Luigi, Docker, Kubernetes, AWS S3, Redshift, Google BigQuery, Dolby Atmos, high-order ambisonics, Tableau, Matplotlib
Preferred qualifications
- Experience integrating data pipelines with AI/ML workflows, including active learning and model retraining.
- Familiarity with audio-specific datasets and metadata management strategies.
- Knowledge of machine learning principles and how data quality affects model performance.
- Experience with distributed training pipelines and large-scale dataset processing.
- Contributions to open-source projects or published research in data science or audio processing.
- Experience using visualization tools such as Tableau and Matplotlib for quality assurance and exploratory analysis.
- Expertise designing systems for AI/ML model monitoring and retraining over time.
